The Role of Neuromodulators in Cortical Plasticity. A Computational Perspective.
The Role of Neuromodulators in Cortical Plasticity. A Computational Perspective.
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神经调节剂在皮质可塑性中的作用。计算观点。
DOI：
10.3389/fnsyn.2016.00038
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发表时间：
2016
影响因子：
3.7
通讯作者：
Clopath C
中科院分区：
文献类型：
--
作者：
Pedrosa V;Clopath C
神经调节剂在调节大脑可塑性方面发挥着无处不在的作用。随着实验技术的最新进展，研究不同神经调节状态在特定大脑区域的作用成为可能。神经调节剂主要通过两种机制影响可塑性：可塑性的门控和神经元活动的上调。然而，这些机制的后果知之甚少，有必要进行实验和理论探索。在这里，我们说明神经调节状态如何通过这两种机制影响皮质可塑性。首先，我们探索神经调节剂通过重塑峰值时间依赖性可塑性的学习窗口来控制可塑性的能力。使用一个简单的计算模型，我们实现了四种不同的学习规则，并证明了它们对感受野可塑性的影响。然后，我们比较了上调学习率和上调神经元活动的神经调节作用。我们发现这些看似相似的机制并没有产生相同的结果：神经元活动的上调可以导致感受野调谐的拓宽或锐化，而学习率的上调只会加强感受野调谐的锐化。这个简单的模型表明需要进一步探索神经调节剂介导的可塑性的丰富景观。未来的实验，加上生物学上详细的计算模型，将阐明神经调节状态调节皮质可塑性的机制的多样性。
Neuromodulators play a ubiquitous role across the brain in regulating plasticity. With recent advances in experimental techniques, it is possible to study the effects of diverse neuromodulatory states in specific brain regions. Neuromodulators are thought to impact plasticity predominantly through two mechanisms: the gating of plasticity and the upregulation of neuronal activity. However, the consequences of these mechanisms are poorly understood and there is a need for both experimental and theoretical exploration. Here we illustrate how neuromodulatory state affects cortical plasticity through these two mechanisms. First, we explore the ability of neuromodulators to gate plasticity by reshaping the learning window for spike-timing-dependent plasticity. Using a simple computational model, we implement four different learning rules and demonstrate their effects on receptive field plasticity. We then compare the neuromodulatory effects of upregulating learning rate versus the effects of upregulating neuronal activity. We find that these seemingly similar mechanisms do not yield the same outcome: upregulating neuronal activity can lead to either a broadening or a sharpening of receptive field tuning, whereas upregulating learning rate only intensifies the sharpening of receptive field tuning. This simple model demonstrates the need for further exploration of the rich landscape of neuromodulator-mediated plasticity. Future experiments, coupled with biologically detailed computational models, will elucidate the diversity of mechanisms by which neuromodulatory state regulates cortical plasticity.